Speaker: Matei Zaharia

Assistant Professor of Computer Science @Stanford and Chief Technologist @Databricks

Matei Zaharia is an assistant professor of computer science at Stanford and Chief Technologist of Databricks, the data and ML infrastructure company based around Apache Spark. He started the Spark project while he was a PhD student at UC Berkeley. He has also contributed to other open source big data systems including Apache Mesos and Apache Hadoop. At Stanford, Matei does research on systems for machine learning as part of the DAWN project.

Find Matei Zaharia at

Proposed Tracks

  • Real-World Data Engineering

    Showcasing DataEng tech and highlighting the strengths of each in real-world applications.

  • Deep Learning Applications & Practices

    Deep learning lessons using Tensorflow, Keras, PyTorch, Caffe across machine translation, computer vision.

  • AI Meets the Physical World

    The track where AI touches the physical world, think drones, ROS, NVidea, TPU and more.

  • Data Architectures You've Always Wondered About

    How did they do that? Real-time predictive pipelines at places like Uber, Self-Driving Cars at Google, Robotic Warehouses from Ocado in the UK, are all possible examples.

  • Applied ML for Software

    Practical machine learning inside the data centers and on software engineering teams.

  • Time Series Patterns & Practices

    Stocks, ad tech/real-time bidding, and anomaly detection. Patterns and practices for more effective Time Series work.